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Automated high-dimensional flow cytometric data analysis

Overview of attention for article published in Proceedings of the National Academy of Sciences of the United States of America, May 2009
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (85th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (59th percentile)

Mentioned by

patent
8 patents
wikipedia
1 Wikipedia page

Citations

dimensions_citation
338 Dimensions

Readers on

mendeley
322 Mendeley
citeulike
11 CiteULike
connotea
1 Connotea
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Title
Automated high-dimensional flow cytometric data analysis
Published in
Proceedings of the National Academy of Sciences of the United States of America, May 2009
DOI 10.1073/pnas.0903028106
Pubmed ID
Authors

Saumyadipta Pyne, Xinli Hu, Kui Wang, Elizabeth Rossin, Tsung-I Lin, Lisa M. Maier, Clare Baecher-Allan, Geoffrey J. McLachlan, Pablo Tamayo, David A. Hafler, Philip L. De Jager, Jill P. Mesirov

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 322 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 22 7%
United Kingdom 4 1%
France 3 <1%
Australia 1 <1%
Israel 1 <1%
Czechia 1 <1%
Colombia 1 <1%
Spain 1 <1%
Germany 1 <1%
Other 2 <1%
Unknown 285 89%

Demographic breakdown

Readers by professional status Count As %
Researcher 92 29%
Student > Ph. D. Student 73 23%
Professor > Associate Professor 30 9%
Student > Master 27 8%
Professor 16 5%
Other 47 15%
Unknown 37 11%
Readers by discipline Count As %
Agricultural and Biological Sciences 102 32%
Medicine and Dentistry 36 11%
Computer Science 32 10%
Biochemistry, Genetics and Molecular Biology 25 8%
Mathematics 22 7%
Other 63 20%
Unknown 42 13%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 9. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 06 December 2022.
All research outputs
#3,799,858
of 25,377,790 outputs
Outputs from Proceedings of the National Academy of Sciences of the United States of America
#37,590
of 102,960 outputs
Outputs of similar age
#14,355
of 120,934 outputs
Outputs of similar age from Proceedings of the National Academy of Sciences of the United States of America
#250
of 677 outputs
Altmetric has tracked 25,377,790 research outputs across all sources so far. Compared to these this one has done well and is in the 83rd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 102,960 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 39.4. This one has gotten more attention than average, scoring higher than 59% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 120,934 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 85% of its contemporaries.
We're also able to compare this research output to 677 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 59% of its contemporaries.